Rightslink® by Copyright Clearance Center

Mel-frequency cepstral coefficients outperform embeddings from pre-trained convolutional neural networks under noisy conditions for discrimination tasks of individual gibbons

Author:

Mohamed Walid Lakdari,Abdul Hamid Ahmad,Sarab Sethi,Gabriel A. Bohn,Dena J. Clink

Publication:

Ecological Informatics

Publisher:

Elsevier

Date:

May 2024

Please select your organization and/or account

Organization

Account

Please select your account from the above dropdown list. These accounts represent the offices, campuses, and other sites where your organization operates. Your account selection should match where you typically have an office or workspace. Even when you are traveling or temporarily working elsewhere, you should select the account that represents where you customarily work.

Cancel OK

Welcome to RightsLink

Elsevier has partnered with Copyright Clearance Center's RightsLink service to offer a variety of options for reusing this content.

Note: This article is available under the Creative Commons CC-BY-NC license and permits non-commercial use, distribution and reproduction in any medium, provided the original work is properly cited.

For commercial reuse, permission must be requested below.

I would like to...This drop down menu contains the options the publisher has agreed to permit for reuse of their copyrighted material. The publisher offers these types of use either directly through RightsLink or after approval by the publisher. Please reference the terms and conditions offered during the order process for a complete understanding of the use you select. Need more info?